Apparatus, system, and method for adaptive asynchronous equalization using leakage

ABSTRACT

An apparatus, system, and method are disclosed for adaptive asynchronous equalization using leakage. An equalizer sums products of a plurality of tap signals from a delay line sampling a read signal and a plurality of corresponding tap coefficients to form an equalized signal in an asynchronous time domain having a first sampling rate. A leaky function module calculates a leaky function for each tap coefficient in the asynchronous time domain. An adaptation module adapts each of the tap coefficients as the leaky function for each tap coefficient summed with a signal-dependent updating function for each tap coefficient.

BACKGROUND OF THE INVENTION

1. Field of the Invention

This invention relates to adaptive equalization and more particularlyrelates to adapting equalization coefficients using leakage.

2. Description of the Related Art

Data processing systems often use magnetic tape for high volume, lowcost data storage. For example, a data processing system may backup thedata from a data storage subsystem comprising a plurality of hard diskdrives to magnetic tape. Large volumes of infrequently used data mayalso be stored to magnetic tape. For example, data intensive geologicalstudy data, meteorological data, or the like may be cost effectivelyarchived on magnetic tape.

A user or software application may retrieve data from the magnetic tapeby mounting the magnetic tape on a magnetic tape drive and reading thedata from the magnetic tape. The magnetic tape drive reads the magnetictape by sensing magnetic polarization changes on the magnetic tape thatencode the data and generates an analog signal from the magneticpolarization changes that embodies the data. The analog read signal issampled and car converted to a plurality of digital values that form adigital read signal.

The digital read signal comprises a plurality of frequency components,each with a magnitude and phase characteristic. Variations in themagnitude and phase characteristics of the frequency components increasethe difficulty of recognizing the data in the digital read signal.

As a result, the magnetic tape drive typically equalizes or adjusts themagnitude and phase characteristic of each frequency component so thatthe data may be more easily recognized and recovered. The magnetic tapedrive often equalizes the digital read signal by storing a plurality ofdigital values in a delay line. The digital values are sampled for aplurality of instances of the read signal with an analog-to-digitalconverter operating at a sampling frequency that is not synchronizedwith respect to the duration of the bits stored on the tape medium. Eachstored digital value or tap signal is multiplied by a coefficient andthe sum of the tap coefficient products forms an equalized signal valuefor a specified instance of the asynchronous sampling clock.

The data may have originally been written by one or more of a variety ofmagnetic tape drives from a variety of manufacturers. In addition, eachmagnetic tape may have originally been written under a wide range ofenvironmental conditions. As a result, when magnetic tapes are read,magnetic tape read signals often exhibit a wide range ofcharacteristics. As a result, the magnetic tape drive must oftendynamically adjust the tap coefficients used to equalize the read backsignal to compensate for differences in the read signal.

Unfortunately, adapting the coefficients of the asynchronous equalizermay cause the equalization function to become unstable. For example,adapting the coefficients may drive one or more coefficients to anexcessive value that destabilizes the equalization function. Therefore,some coefficient values may be frozen at specified values. Freezingcoefficients reduces the probability that the equalization function willbecome unstable, but also reduces the equalization function's ability toadapt to differing read signal characteristics.

In addition, adapting equalization coefficients of an asynchronousequalizer often increases the strength of higher frequencies that do notinclude significant signal elements. As a result, the high-frequencynoise of the read signal is increased, reducing the tape drives abilityto recognize and retrieve data from the read signal.

From the foregoing discussion, it should be apparent that a need existsfor an apparatus, system, and method that adapt equalizationcoefficients while maintaining equalization function stability for anasynchronous equalizer. Beneficially, such an apparatus, system, andmethod would increase the asynchronous equalization function's abilityto adapt to different read signals.

SUMMARY OF THE INVENTION

The present invention has been developed in response to the presentstate of the art, and in particular, in response to the problems andneeds in the art that have not yet been fully solved by currentlyavailable tap coefficient adaptation methods. Accordingly, the presentinvention has been developed to provide an apparatus, system, and methodfor adapting tap coefficients that overcome many or all of theabove-discussed shortcomings in the art.

The apparatus to adapt tap coefficients is provided with a plurality ofmodules configured to functionally execute the necessary steps ofsumming products of tap signals and tap coefficients to form anequalized signal, calculating a leaky function for each tap coefficient,and adapting each tap coefficient as a leaky function summed with asignal-dependent updating function. These modules in the describedembodiments include an equalizer, a leaky function module, and anadaptation module. In addition, the apparatus includes asignal-dependent updating function module and a delay line.

The analog-to-digital converter (“ADC”) samples a read signal at a firstinstance and stores the first instance sample in a first register of adelay line. The read signal is sampled in an asynchronous time domainhaving a first sampling rate. In one embodiment, the first sampling rateover samples a read signal to form the digital read signal. Subsequentlythe ADC samples the read signal at a second instance and stores thesecond instance sample in the first register while copying the firstinstance sample to a second register. The ADC repeatedly samples theread signal, storing a plurality of samples in a plurality of registers.Each sample is available as a plurality of tap signals. The equalizersums products of the plurality of tap signals and a plurality ofcorresponding tap coefficients to form an equalized signal in theasynchronous time domain.

The leaky function module calculates a leaky function for each tapcoefficient in the asynchronous time domain. In one embodiment, theleaky function is the tap coefficient minus a function of the tapcoefficient multiplied by a small constant.

In one embodiment, the signal-dependent updating function modulecalculates an error signal for each tap signal in a synchronous timedomain having a second sampling rate. Each error signal may becalculated as the difference between the equalized signal interpolatedinto the synchronous time domain and an estimated signal. In a certainembodiment, the estimated signal is calculated from the equalized signalinterpolated into the synchronous time domain and has a target signaltype. In one embodiment, the target signal type is partial responseclass-4 (“PR4”) signal. In a certain embodiment, the signal-dependentupdating function is a minus constant multiplied by the error signal andthe tap signal for each tap signal.

The adaptation module adapts each of the tap coefficients as the leakyfunction for each tap coefficient summed in the asynchronous time domainwith the signal-dependent updating function for each tap coefficientinterpolated into the asynchronous time domain. The apparatus adapts thetap coefficients, allowing the equalizer to adapt to changes in readsignal characteristics.

A system of the present invention is also presented to adapt tapcoefficients. The system may be embodied in a data storage device suchas a magnetic tape drive. In particular, the system, in one embodiment,includes a communication module, a control module, a write channelmodule, a write head, and a read channel module comprising an equalizer,a leaky function module, and an adaptation module.

The control module controls the operation of the system. Thecommunication module communicates with a host such as a storage devicecontroller. The host stores data to the system and retrieves data fromthe system. The host may communicate data to the system through thecommunication module. The control module may direct the write channelmodule to record the data as an analog signal through the write head tothe storage media.

The host may further communicate a request to retrieve data from thesystem through the communication module. The control module may directthe read channel module to process a read signal received from aspecified portion of the storage media through the read head. Theequalizer sums products of a plurality of tap signals from a delay linestoring the digitized read signals and a plurality of corresponding tapcoefficients to form an equalized signal in an asynchronous time domainhaving a first sampling rate. The leaky function module calculates aleaky function for each tap coefficient in the asynchronous time domain.The adaptation module adapts each of the tap coefficients as the leakyfunction for each tap coefficient summed with a signal-dependentupdating function for each tap coefficient calculated in a synchronoustime domain having a second sampling rate and interpolated into theasynchronous time domain. The system adapts the tap coefficients tosupport changes in read signal characteristics while stabilizingcoefficient drift.

A method of the present invention is also presented for adapting tapcoefficients. The method in the disclosed embodiments substantiallyincludes the steps necessary to carry out the functions presented abovewith respect to the operation of the described apparatus and system. Inone embodiment, the method includes summing products of tap signals andtap coefficients to form an equalized signal, calculating a leakyfunction for each tap coefficient, and adapting each tap coefficient asa leaky function summed with a signal-dependent updating function.

An equalizer sums products of a plurality of tap signals from a delayline storing digital read signals and a plurality of corresponding tapcoefficients to form an equalized signal in an asynchronous time domainhaving a first sampling rate. A leaky function module calculates a leakyfunction for each tap coefficient in the asynchronous time domain. Anadaptation module adapts each of the tap coefficients as the leakyfunction for each tap coefficient summed with a signal-dependentupdating function for each tap coefficient. The method adapts the tapcoefficients to allow the equalizer to adapt to changes in read signalcharacteristics while stabilizing coefficient drift. In addition, themethod may attenuate higher frequency signals with low signal energy toimprove a signal to noise ratio of the digital read signal.

Reference throughout this specification to features, advantages, orsimilar language does not imply that all of the features and advantagesthat may be realized with the present invention should be or are in anysingle embodiment of the invention. Rather, language referring to thefeatures and advantages is understood to mean that a specific feature,advantage, or characteristic described in connection with an embodimentis included in at least one embodiment of the present invention. Thus,discussion of the features and advantages, and similar language,throughout this specification may, but do not necessarily, refer to thesame embodiment.

Furthermore, the described features, advantages, and characteristics ofthe invention may be combined in any suitable manner in one or moreembodiments. One skilled in the relevant art will recognize that theinvention may be practiced without one or more of the specific featuresor advantages of a particular embodiment. In other instances, additionalfeatures and advantages may be recognized in certain embodiments thatmay not be present in all embodiments of the invention.

The embodiment of the present invention adapts tap coefficients using aleaky function allowing an asynchronously operating equalizer to adaptto changing read signal characteristics while stabilizing tapcoefficient drift. In addition, the embodiment of the present inventionsupports the attenuation of higher frequency signals with low signalenergy. These features and advantages of the present invention willbecome more fully apparent from the following description and appendedclaims, or may be learned by the practice of the invention as set forthhereinafter.

BRIEF DESCRIPTION OF THE DRAWINGS

In order that the advantages of the invention will be readilyunderstood, a more particular description of the invention brieflydescribed above will be rendered by reference to specific embodimentsthat are illustrated in the appended drawings. Understanding that thesedrawings depict only typical embodiments of the invention and are nottherefore to be considered to be limiting of its scope, the inventionwill be described and explained with additional specificity and detailthrough the use of the accompanying drawings, in which:

FIG. 1 is a schematic block diagram illustrating one embodiment of adata storage system in accordance with the present invention;

FIG. 2 is a schematic block diagram illustrating one embodiment of asampling module of the present invention;

FIG. 3 is a schematic block diagram illustrating one embodiment of aread channel of the present invention;

FIG. 4 is a schematic block diagram illustrating one alternateembodiment of a read channel of the present invention;

FIG. 5 is a schematic block diagram illustrating one embodiment of aleakage adaptation apparatus of the present invention;

FIG. 6 is a schematic block diagram illustrating one embodiment of anequalization adaptation module of the present invention;

FIG. 7 is a schematic block diagram illustrating one alternateembodiment of an equalization adaptation module of the presentinvention;

FIG. 8 is a schematic flow chart diagram illustrating one embodiment ofa leaky adaptation method of the present invention;

FIG. 9 is a schematic flow chart diagram illustrating one embodiment ofa coefficient fixing method in accordance with the present invention;

FIG. 10 is a graph illustrating one embodiment of coefficient adaptationwithout leakage;

FIG. 11 is a graph illustrating one embodiment of frequency responsewithout leakage;

FIG. 12 is a graph illustrating one embodiment of coefficient adaptationof the present invention; and

FIG. 13 is a graph illustrating one embodiment of frequency response ofthe present invention.

DETAILED DESCRIPTION OF THE INVENTION

Many of the functional units described in this specification have beenlabeled as modules, in order to more particularly emphasize theirimplementation independence. For example, a module may be implemented asa hardware circuit comprising custom VLSI circuits or gate arrays,off-the-shelf semiconductors such as logic chips, transistors, or otherdiscrete components. A module may also be implemented in programmablehardware devices such as field programmable gate arrays, programmablearray logic, programmable logic devices or the like.

Modules may also be implemented in software for execution by varioustypes of processors. An identified module of executable code may, forinstance, comprise one or more physical or logical blocks of computerinstructions, which may, for instance, be organized as an object,procedure, or function. Nevertheless, the executables of an identifiedmodule need not be physically located together, but may comprisedisparate instructions stored in different locations which, when joinedlogically together, comprise the module and achieve the stated purposefor the module.

Indeed, a module of executable code may be a single instruction, or manyinstructions, and may even be distributed over several different codesegments, among different programs, and across several memory devices.Similarly, operational data may be identified and illustrated hereinwithin modules, and may be embodied in any suitable form and organizedwithin any suitable type of data structure. The operational data may becollected as a single data set, or may be distributed over differentlocations including over different storage devices, and may exist, atleast partially, merely as electronic signals on a system or network.

Reference throughout this specification to “one embodiment,” “anembodiment,” or similar language means that a particular feature,structure, or characteristic described in connection with the embodimentis included in at least one embodiment of the present invention. Thus,appearances of the phrases “in one embodiment,” “in an embodiment,” andsimilar language throughout this specification may, but do notnecessarily, all refer to the same embodiment.

Reference to a computer readable medium may take any form capable ofcausing execution of a program of machine-readable instructions on adigital processing apparatus. A computer readable medium may be embodiedby a compact disk, digital-video disk, a magnetic tape, a Bernoullidrive, a magnetic disk, a punch card, flash memory, integrated circuits,or other digital processing apparatus memory device.

Furthermore, the described features, structures, or characteristics ofthe invention may be combined in any suitable manner in one or moreembodiments. In the following description, numerous specific details areprovided, such as examples of programming, software modules, userselections, network transactions, database queries, database structures,hardware modules, hardware circuits, hardware chips, etc., to provide athorough understanding of embodiments of the invention. One skilled inthe relevant art will recognize, however, that the invention may bepracticed without one or more of the specific details, or with othermethods, components, materials, and so forth. In other instances,well-known structures, materials, or operations are not shown ordescribed in detail to avoid obscuring aspects of the invention.

FIG. 1 is a schematic block diagram illustrating one embodiment of adata storage system 100 of the present invention. The system 100includes a data storage device 150 comprising a communication module105, a control module 145, a read/write module 110 that includes a writechannel module 115 and a read channel module 120, a head assembly 135comprising a write head 125 and a read head 130, and a storage media140. In one embodiment, the system further includes a host 155.

The control module 145 controls the operation of the data storage device150. In one embodiment, the control module 145 includes a random accessmemory storing instructions executed on a processor as is well known tothose skilled in the art. The communication module 105, read/writemodule 110, head assembly 135, and storage media 140 may operateresponsive to commands from the control module 145.

The communication module 105 communicates with the host 155. The hostmay be a storage device controller, a mainframe computer, a networkrouter, or the like. The communication module 105 may comprise anEthernet interface or a Fibre Channel interface. The host 155 storesdata to the data storage device 150 and retrieves data from the datastorage device 150. The host 155 may communicate data to the datastorage device 150 through the communication module 105. The controlmodule 145 may direct the write channel module 115 to record the data asan analog signal through the write head 125 to the storage media 140.

The host 155 may further communicate a request to retrieve data from thedata storage device 150 through the communication module 105. Thecontrol module 145 may direct the read channel module 120 to process ananalog read signal or read signal received from a specified portion ofthe storage media 140 through the read head 130. The read channel module120 converts the read signal into a plurality of digital samples forminga digital read signal and identifies data from the digital read signal.

FIG. 2 is a schematic block diagram illustrating one embodiment of asampling module 200 of the present invention. The sampling module 200may be incorporated within the read channel module 120 of FIG. 1 in amanner that will be con described hereafter. In addition, thedescription of FIG. 2 may refer to elements of FIG. 1, like numbersreferring to like elements. The sampling module 200 includes an analogto digital converter (“ADC”) 205, one or more registers 210, a readsignal 215, and one or more tap signals 220. Although for simplicityfour registers 210 are depicted, any number of registers 210 may beemployed.

The read signal 215 is the analog read signal from the read head 130 ofFIG. 1. The ADC 205 samples the read signal 215, generating a digitalvalue representing the analog voltage of the read signal 215 as is wellknow to those skilled in the art. In addition, the ADC 205 samples theread signal in an asynchronous time domain. In one embodiment, theasynchronous time domain employs a first sampling rate. A first register210 a stores the digital value generated by the ADC 205. In oneembodiment, a first clock signal 225 oscillating at the first samplingrate loads the digital value into the first register 210 a.

In addition, the first clock signal 225 loads each register 210 at thefirst sampling rate. Thus the first register 210 a loads a first digitalvalue during a first instance of the first clock signal 225, while asecond register 210 b loads the first digital value from the firstregister 210 a as the first register 210 a loads a second digital valuefrom the ADC 205 during a second instance of the first clock signal 225.Thus each register 210 stores a digital value of the read signal 215sampled during a progressively earlier sample interval. The registers210 may be referred to collectively as a delay line 230. The digitalvalue of each register 210 is available as a tap signal 220. Each tapsignal 220 represents the digital value of a specified instance of theread signal 215.

FIG. 3 is a schematic block diagram illustrating one embodiment of aread channel 300 of the present invention. The description refers toelements of FIGS. 1-2, like numbers referring to like elements. The readchannel 300 includes the sampling module 200 of FIG. 2, and an equalizer320, first interpolator 330 a, sequence detector 345, signal computationmodule 350, gain control 340, timing control 335, second interpolator330 b, and equalizer adaptation module 325.

The sampling module 200 samples the read signal 215 and outputs aplurality of tap signals 220 as described in FIG. 2. The equalizer 320sums a product of each tap signal 220 and a corresponding tapcoefficient 360 to form an equalized signal 365. In addition, theequalizer 320 sums the products in the asynchronous time domain 302described in FIG. 2.

The first interpolator 330 a interpolates the equalized signal 365 fromthe asynchronous time domain 302 into a synchronous time domain 304 as asynchronous equalized signal 375. The synchronous time domain 304employs a second sampling rate. The second sampling rate may be asymbol-sampling rate such as the sample rate corresponding to theinverse of a data bit duration. In one embodiment, the first samplingrate is greater than the second sampling rate.

The multiplier 362 multiples the synchronous equalized signal 375 by again factor specified by the gain control 340 to form an amplifiedequalized signal 385. The sequence detector 345 detects data 315 fromthe amplified equalized signal 385. In one embodiment, the sequencedetector 345 is configured as a maximum likelihood detector as is wellknown to those skilled in the art.

In one embodiment, the signal computation module 350 calculates anestimated signal 390 from the sequence detector 345. In addition, thesignal computation module 350 may calculate the estimated signal 390such that the estimated signal 390 has a target signal type. The targetsignal type may correspond to a (1−D²) PR4 polynomial, where D denotes adelay by one symbol interval, a (1+D−D²−D³) extended PR4 (“EPR4”)polynomial, a (1+2D−2D³−D⁴) extended EPR4 (“EEPR4”) polynomial, ageneralized partial-response (“GPR”) polynomial with nonintegercoefficients, and a GPR polynomial for noise-predictivemaximum-likelihood (“NPML”) detection as is well known to those skilledin the art.

The subtractor 355 calculates a synchronous error signal 380 for eachtap coefficient 360 as the difference between the estimated signal 390and the synchronous equalized signal 375. The second interpolator 330 binterpolates each synchronous error signal 380 into the asynchronoustime domain 302 as an error signal 370.

The equalizer adaptation module 325 adapts each tap coefficient 360 as aleaky function of each tap coefficient 360 summed with a signaldependent updating function of the tap signal 220 and the error signal370. The equalizer 320 employs the adapted tap coefficients 360 inequalizing the read signal 215.

FIG. 4 is a schematic block diagram illustrating one alternateembodiment of a read channel 400 of the present invention. The readchannel 400 includes the elements of FIG. 3, like numbers indicatinglike elements, performing the functions of depicted in FIG. 3, exceptthat the subtractor 355 calculates the synchronous error signal 380 foreach tap coefficient 360 as the difference between the estimated signal390 and the amplified equalized signal 385.

FIG. 5 is a schematic block diagram illustrating one embodiment of aleakage adaptation apparatus 500 of the present invention. The apparatus500 may be incorporated within the read channels 300, 400 of FIGS. 3 and4 in a manner that will be described hereafter. Elements of FIGS. 1-4are referred to herein, like numbers referring to like elements. Asdepicted, the apparatus 500 includes a leaky function module 505,signal-dependent updating function module 510, estimated signal module515, adaptation module 520, initial coefficient module 525, andequalizer 320.

In one embodiment, the equalizer adaptation module 325 of FIGS. 3 and 4embodies the leaky function module 505, the adaptation module 520, andthe initial coefficient module 525. The sequence detector 345 and signalcomputation module 350 of FIGS. 3 and 4 may also embody the estimatedsignal module 515. The equalizer 320 is the equalizer 320 of FIGS. 3 and4. The subtractor 355, second interpolator 330 b, and equalizeradaptation module 325 may embody the signal-dependent updating functionmodule 510.

The equalizer 320 sums products of the tap signals 220 and thecorresponding tap coefficients 360 to form the equalized signal 365 inthe asynchronous time domain 302. The leaky function module 505calculates a leaky function for each tap coefficient 360 in theasynchronous time domain 302.

In one embodiment, the signal-dependent updating function module 510calculates the synchronous error signal 380 for each tap signal 220 inthe synchronous time domain 304. The signal-dependent updating functionmodule 510 may calculate each synchronous error signal 380 as thedifference between the estimated signal 390 and the synchronousequalized signal 375. In an alternate embodiment, the signal-dependentupdating function module 510 calculates each synchronous error signal380 as the difference between the estimated signal 390 and the amplifiedequalized signal 385. In a certain embodiment, the signal-dependentupdating function 510 is a minus constant multiplied by the product ofthe synchronous error signal 380 interpolated into the asynchronous timedomain 302 as the error signal 370 and the tap signal 220.

In a certain embodiment, the estimated signal module 515 calculates theestimated signal 390 from the synchronous equalized signal 375. Inaddition, the estimated signal module 515 may calculate the estimatedsignal 390 from the amplified equalized signal 385. Furthermore, theestimated signal module 515 may calculate the estimated signal 390 fromthe sequence detector 345. The estimated signal module 515 calculatesthe estimated signal 390 with a target signal type.

The adaptation module 520 adapts each of the tap coefficients 360 as theleaky function for each tap coefficient 360 summed in the asynchronoustime domain 302 with the signal-dependent updating function for each tapcoefficient 360. In one embodiment, the initial coefficient module 525initializes each tap coefficient 360 to a specified initial value. Theapparatus 500 adapts the tap coefficients 360, allowing the equalizer320 to adapt to changes in read signal 215 characteristics.

FIG. 6 is a schematic block diagram illustrating one embodiment of anequalization adaptation module 325 of FIGS. 3 and 4. The equalizationadaptation module 325 embodies the leaky function module 505,signal-dependent updating function module 510, and adaptation module 520of FIG. 5 in a manner that will be described hereafter. In addition,FIG. 6 refers to elements of FIGS. 1-5, like numbers referring to likeelements. All signals and operations employ digital values andarithmetic as is well known to those skilled in the art.

With a first multiplexer 622 a, the error signal 370 selects the tapsignal 220 if the sign of the error signal 370 is a positive value, orthe tap signal 220 multiplied by the value minus one (−1) 610 if theerror signal 370 is a negative value, or the value zero (0) 615 if theerror signal 370 is equivalent to zero (0). Thus the result of the firstmultiplexer 622 a is equivalent to multiplying the tap signal 220 withthe sign of the error signal 370 provided that the error signal 370 isnonzero. Otherwise, the result is equivalent to multiplying the tapsignal 220 by a zero (0) error signal. The output of the firstmultiplexer 622 a is multiplied by either eight (8), four (4), or (2)two by shifting the first multiplexer 622 a output by three positions,two positions or one position to more significant positions,respectively, as shown by boxes 630, or multiplied by one, depending onthe value of the parameter α 635 that controls the selection of theinput to a second multiplexer 622 b.

The tap coefficient 360 is divided by either eight (8), four (4), or (2)by shifting the tap coefficient by 3 positions, 2 positions or 1position to the right, respectively, as shown by boxes 650, ormultiplied by one, depending on the value of the parameter αμ 655 thatcontrols the input of a third multiplexer 622 c. A multiplier 624multiplies the output of the third multiplexer 622 c with the binaryvalue EN_LEAKAGE 640. A first summer 660 sums the output of the secondmultiplexer 622 b and the multiplier 624. If EN_LEAKAGE 640 is one (1),the leakage output signal of the third multiplexer 622 c is enabled.Alternatively, if EN_LEAKAGE 640 is zero (0), the leakage output signalof the third multiplexer 622 c is zero (0) or not enabled.

A second summer 670 sums the output of the first summer 660 with theoutput of an accumulation register 690. A carry control module 665selects an input of a fourth and fifth multiplexer 622 d, 622 e. If theoutput of the second summer 670 is a saturated value wherein the digitalvalue of the output exceeds the largest magnitude value that may berepresented by the output, the carry control module 665 directs thefifth multiplexer 622 e to select either the −ACCMAX 675 or +ACCMAX 680values. The values −ACCMAX 675 or +ACCMAX 680 are a specified value suchthat the output of the fifth multiplexer 622 e is an appropriate valuesuch as all digital zeros or all digital ones when the output of thesecond summer 670 is saturated. The output of the fifth multiplexer 622e is stored in the accumulation register 690.

In addition, the carry control module 665 directs the fourth multiplexer622 d to select either the most significant bits (“MSB”) of the tapcoefficient 685, the tap coefficient MSB 685 plus one (1) 695, or thetap coefficient MSB 685 plus minus one (−1) 607. The output of thefourth multiplexer 622 d is the adapted tap coefficient MSB 612 whilethe output of the accumulation register 690 is the adapted tapcoefficient least-significant bits (“LSB”) 614. The depicted equalizeradaptation module 325 may be replicated for each tap coefficient 360. Inaddition, the depicted equalizer adaptation module 325 reduces thesemiconductor gates required to perform the operations of the equalizeradaptation module 325.

FIG. 7 is a schematic block diagram illustrating one alternateembodiment of an equalizer adaptation module 325 of the presentinvention. The module 325 may be an alternate embodiment of theequalizer adaptation module 325 of FIGS. 3 and 4. The module 325includes a processor module 705, a memory module 710, and a bridgemodule 715. In addition, the module 325 is depicted in communicationwith the ADC 205 of FIG. 2 and the equalizer 320 and second interpolator330 b of FIGS. 3 and 4.

The processor module 705, memory module 710, and bridge module 715 maybe fabricated of semiconductor gates on one or more semiconductorsubstrates. Each semiconductor substrate may be packaged in one or moresemiconductor devices mounted on circuit cards. Connections between theprocessor module 705, the memory module 710, and the bridge module 715may be through semiconductor metal layers, substrate to substratewiring, or circuit card traces or wires connecting the semiconductordevices.

The memory module 710 stores software instructions and data. Theprocessor module 705 executes the software instructions and manipulatesthe data as is well known to those skilled in the art. The processormodule 705 communicates with the ADC 205, the equalizer 320, and thesecond interpolator 330 b through the bridge module 715. In oneembodiment, the memory module 710 stores and the processor module 705executes one or more software processes embodying the leaky functionmodule 505, signal-dependent updating function module 510, estimatedsignal module 515, adaptation module 325, and initial coefficient module525 of FIG. 5.

The schematic flow chart diagrams that follow are generally set forth aslogical flow chart diagrams. As such, the depicted order and labeledsteps are indicative of one embodiment of the presented method. Othersteps and methods may be conceived that are equivalent in function,logic, or effect to one or more steps, or portions thereof, of theillustrated method. Additionally, the format and symbols employed areprovided to explain the logical steps of the method and are understoodnot to limit the scope of the method. Although various arrow types andline types may be employed in the flow chart diagrams, they areunderstood not to limit the scope of the corresponding method. Indeed,some arrows or other connectors may be used to indicate only the logicalflow of the method. For instance, an arrow may indicate a waiting ormonitoring period of unspecified duration between enumerated steps ofthe depicted method. Additionally, the order in which a particularmethod occurs may or may not strictly adhere to the order of thecorresponding steps shown.

FIG. 8 is a schematic flow chart diagram illustrating one embodiment ofa leaky adaptation method 800 of the present invention. The method 800substantially includes the steps necessary to carry out the functionspresented above with respect to the operation of the described system100, 300, 400, and apparatus 200, 500 600, 700 of FIGS. 1-7. Inaddition, the description of FIG. 8 references elements of FIGS. 1-7,like numbers referring to like elements.

The method 800 begins and in one embodiment, the initial coefficientmodule 525 initializes 805 the tap coefficients 360 to initial values.The initial coefficient module 525 may initialize 805 each tapcoefficient 360 to a value specified for the tap coefficient 360.Alternatively, the initial coefficient module 525 may initialize 805 alltap coefficients to a common initial value.

In one embodiment, the ADC 205 samples 810 the read signal 215 to thedelay line 230 in the asynchronous time domain 302. The equalizer 320sums 815 products of the tap signals 220 from the delay line 230 and thecorresponding tap coefficients 360 to form the equalized signal 365 inthe asynchronous time domain 302. In one embodiment, the equalizer 320employs Equation 1, where c_(i,n) is the tap coefficient 360 for eachtap signal 220 i at time index n, x_(i) is the tap signal 220 for eachi, and N is the number of tap signals 220.

$\begin{matrix}{Z_{n} = {\sum\limits_{i = 0}^{N - 1}{c_{i,n}x_{n - i}}}} & {{Equation}\mspace{14mu} 1}\end{matrix}$

The first interpolation module 330 a interpolates 820 the equalizedsignal 365 into the synchronous time domain 304 as the synchronousequalized signal 375. In one embodiment, the first interpolation module330 a interpolates 820 the equalized signal 365 as a weighted average ofa first equalized signal 365 and a second equalized signal 365. Forexample, if the first equalized signal 365 is available at the firstclock signal 225 of the first sample rate twenty nanoseconds (20 ns)before a clock of the second sample rate while the second equalizedsignal 365 is available ten nanoseconds (10 ns) after the clock of thesecond sample rate, the first interpolation module 330 a may calculatethe synchronous equalized signal 375 as two times the second equalizedsignal 365 plus the first equalized signal 365 all divided by three.

In one embodiment, the estimated signal module 515 calculates 825 theestimated signal 390 from the synchronous equalized signal 375. In analternate embodiment, the estimated signal module 515 calculates 825 theestimated signal 390 from the amplified equalized signal 385. In anotheralternate embodiment, the estimated signal module 515 calculates 825 theestimated signal 390 from the sequence detector 345. The estimatedsignal module 515 calculates 825 the estimated signal 390 as a targetsignal type. The target signal type may be specified by a PR4polynomial, an EPR4 polynomial, an EEPR4 polynomial, a GPR polynomialwith noninteger coefficients, and a GPR polynomial for NPML detection asis well known to those skilled in the art.

In one embodiment, the signal-dependent updating function module 510calculates 828 a synchronous error signal 380 for each tap signal 220.In a certain embodiment, the signal-dependent updating function module510 calculates 828 the synchronous error signal 380 as the estimatedsignal 390 minus the synchronous equalized signal 375. In an alternateembodiment, the signal-dependent updating function module 510 calculates828 the synchronous error signal 380 as the estimated signal 390 minusthe amplified equalized signal 385.

In one embodiment, the second interpolation module 330 b interpolates830 the synchronous error signal 380 into the asynchronous time domain302 as the error signal 370. The second interpolation module 330 b mayinterpolate 830 the error signal 370 as the weighted average of one ormore error signal values of the synchronous error signal 380.

In one embodiment, the signal-dependent updating function module 510calculates 835 the signal-dependent updating function for each tapcoefficient 360 using Equation 2, where α 635 is a constant parameter,e_(n) is the error signal 370, and x_(n−i) is the tap signal 220.(−αe_(n)x_(n−i))  Equation 2

The leaky function module 505 calculates 840 a leaky function for eachtap coefficient in the asynchronous time domain 302. In one embodiment,the leaky function is calculated 840 using Equation 3, where μ is aconstant parameter, and ƒ(c_(i,n)) is a coefficient function of the tapcoefficient c_(i,n) 360 for the tap signal 220.c_(i,n)−αμƒ(c_(i,n))  Equation 3

In one embodiment, αμ is in the range of 0.0001 to 0.2. The value αμcontrols the tap leakage process by determining the amount of leakage.Thus, the larger the value of αμ the larger the leakage. In a certainembodiment, the coefficient function ƒ(c_(i,n)) is calculated usingEquation 4. In an alternate embodiment, function ƒ(c_(i,n)) iscalculated using Equation 5.ƒ(c _(i,n))=c _(i,n)  Equation 4ƒ(c _(i,n))=sgn(c _(i,n))  Equation 5

The adaptation module 520 adapts 845 each of the tap coefficients 360 asthe leaky function for each tap coefficient summed with thesignal-dependent updating function for each tap coefficient. In oneembodiment, the adaptation module 520 adapts 845 each tap coefficient360 using Equation 6 where n+1 indicates the tap coefficient for a nextsampling interval.c _(i,n+1) =c _(i,n)−αμƒ(c _(i,n))−αe _(n) x _(n−i)  Equation 6

In addition, the adaptation module 520 may determine 850 if the leakyadaptation method 800 terminates. If the adaptation module 520determines 850 the method 800 does not terminate, the method 800 loopsand the ADC 205 samples 810 the read signal 215. If the adaptationmodule 520 determines 850 the method 800 terminates, the method 800ends. The method 800 adapts 845 the tap coefficients 360 to allow theequalizer 320 to adapt to changes in read signal 215 characteristicswhile stabilizing tap coefficient 360 drift.

FIG. 9 is a schematic flow chart diagram illustrating one embodiment ofa coefficient fixing method 900 in accordance with the presentinvention. The method 900 substantially includes the steps necessary tocarry out the functions presented above with respect to the operation ofthe described system 100, 300, 400, apparatus 200, 500 600, 700, andmethod 800 of FIGS. 1-8. In addition, the description of FIG. 9references elements of FIGS. 1-7, like numbers referring to likeelements.

The method 900 begins and in one embodiment, the adaptation module 520determines 905 if a tap coefficient 360 is fixed. If the adaptationmodule 520 determines 905 the tap coefficient 360 is not fixed, theadaptation module 520 adapts 910 the tap coefficient 360 as described bythe method 800 of FIG. 8 and the method 900 ends. For example, theadaptation module 520 may adapt 910 the tap coefficient 360 usingEquation 6.

If the adaptation module 520 determines 905 the tap coefficient 360 isfixed, the adaptation module 520 sets 915 the tap coefficient 360 equalto the tap coefficient 360 itself and the method 900 ends. In oneembodiment, the adaptation module 520 employs Equation 7 to set 915 thetap coefficient 360 equal to itself.c_(i,n+1)=c_(i,n)  Equation 7

Equalizer functions have traditionally fixed one or more tapcoefficients 360 to increase the stability of the equalizer function bypreventing the equalizer function from adapting to an extreme orunstable state. The present invention may reduce the number of tapcoefficients 360 that must be fixed to maintain equalizer functionstability as the leaky function moderates any increase in the value ofeach tap coefficient 360.

FIG. 10 is a graph 1000 illustrating one embodiment of coefficientadaptation without leakage. The graph 1000 shows the coefficient values1005 of one or more tap coefficients 360 for a progressive number ofadaptation iterations 1010. A first and second tap coefficient 360 a,360 b are initialized to a first and second initial value 1025 a, 1025 brespectively. The tap coefficients 360 are subsequently adapted withoutleakage. The absolute coefficient values 1005 of the tap coefficients360 increase until the coefficient values 1005 of the tap coefficients360 are constrained by upper and lower bounds 1015, 1020. The upper andlower bounds 1015, 1020 may be established to stabilize an equalizerfunction.

FIG. 11 is a graph 1100 illustrating one embodiment of frequencyresponse without leakage. The graph 1100 shows the response magnitude1105 of an equalized signal 1115 over a normalized frequency range 1110.The equalized signal 1115 is calculated with tap coefficients 360 thatare adapted without leakage. The graph 1100 depicts a high responsemagnitude 1120 for higher frequencies although there is little or noenergy in the signal at the higher frequencies. The adaptation of thetap coefficients 360 without leakage results in a high response for lowenergy, high frequency equalized signal 1115 components.

FIG. 12 is a graph 1200 illustrating one embodiment of coefficientadaptation of the present invention. The graph 1200 may be the graph1000 of FIG. 10 with a modified coefficient value 1005 scale such thatthe upper and lower bounds 1015, 1020 represent the same coefficientvalues 1005 of FIG. 10. As depicted, the first and second tapcoefficients 360 a, 360 b are initialized to the first and secondinitial value 1025 a, 1025 b respectively. The tap coefficients 360 aresubsequently adapted with a leaky function of the embodiment of thepresent invention. The leaky function constrains the energy of thecoefficient values 1005 of the tap coefficients 360 and the tapcoefficients 360 converge on stable values.

FIG. 13 is a graph 1300 illustrating one embodiment of frequencyresponse of the present invention. The graph 1300 maybe the graph 1100of FIG. 11 with an equalized signal 365 calculated with tap coefficients360 adapted 845 using leakage. As depicted, a higher frequency response1305 rolls off. The high frequency response 1305 corresponds to a lowenergy of high frequency components of the read signal 215.

The embodiment of the present invention adapts 845 tap coefficients 360using a leaky function allowing an asynchronous equalizer 320 to adaptto changing read signal 215 characteristics while stabilizing tapcoefficient 360 drift. In addition, the embodiment of the presentinvention supports the attenuation of higher frequency signals with lowsignal energy.

The present invention may be embodied in other specific forms withoutdeparting from its spirit or essential characteristics. The describedembodiments are to be considered in all respects only as illustrativeand not restrictive. The scope of the invention is, therefore, indicatedby the appended claims rather than by the foregoing description. Allchanges which come within the meaning and range of equivalency of theclaims are to be embraced within their scope.

1. An apparatus to adapt tap coefficients, the apparatus comprising: anequalizer configured to sum products of a plurality of tap signals froma delay line sampling a read signal and a plurality of corresponding tapcoefficients to form an equalized signal in an asynchronous time domainhaving a first sampling rate; a leaky function module configured tocalculate a leaky function for each tap coefficient in the asynchronoustime domain; and an adaptation module configured to adapt each of thetap coefficients as the leaky function for each tap coefficient summedwith a signal-dependent updating function for each tap coefficientcalculated in a synchronous time domain having a second sampling rateand interpolated into the asynchronous time domain.
 2. The apparatus ofclaim 1, further comprising a signal-dependent updating function moduleconfigured to calculate an error signal for each tap signal as thedifference between the equalized signal interpolated into thesynchronous time domain and an estimated signal.
 3. The apparatus ofclaim 2, further comprising an estimated signal module configured tocalculate the estimated signal from the equalized signal interpolatedinto the synchronous time domain wherein the equalized signal has atarget signal type selected from a (1−D²) partial response class-4(“PR4”) polynomial, where D denotes a delay by one symbol interval, a(1+D−D²−D³) extended PR4 (“EPR4”) polynomial, a (1+2D−2D³−D⁴) extendedEPR4 (“EEPR4”) polynomial, a generalized partial-response (“GPR”)polynomial with noninteger coefficients, and a GPR polynomial fornoise-predictive maximum-likelihood (“NPML”) detection.
 4. The apparatusof claim 2, wherein the signal-dependent updating function is(−αe_(n)x_(n−i)) where α is a constant parameter, e_(n) is the errorsignal for the tap signal, and x_(n−i) is the tap signal, and whereinthe leaky function of each tap coefficient is c_(i,n)−αμƒ(c_(i,n)) whereμ is a constant parameter, and ƒ(c_(i,n)) is a coefficient function ofthe tap coefficient c_(i,n) for the tap signal.
 5. The apparatus ofclaim 4, wherein the coefficient function ƒ(c_(i,n)) is equal toc_(i,n).
 6. The apparatus of claim 4, wherein the coefficient functionƒ(c_(i,n)) is equal to the sign of c_(i,n).
 7. The apparatus of claim 4,wherein μ is selected so that αμ is in the range of 0.0001 to 0.2 and αμcontrols a tap leakage process.
 8. The apparatus of claim 1, wherein thefirst sampling rate is greater than the second sampling rate and thesecond sampling rate is a symbol-sampling rate.
 9. A system to adapt tapcoefficients, the system comprising: a communication module configuredto communicate with a host; a control module configured to controlsystem functions; a write channel module configured to write data to astorage media through a write head; a read channel module configured toread data from the storage media through a read head and comprising anequalizer configured to sum products of a plurality of tap signals froma delay line sampling a read signal from the read head and a pluralityof corresponding tap coefficients to form an equalized signal in anasynchronous time domain having a first sampling rate; a leaky functionmodule configured to calculate a leaky function for each tap coefficientin the asynchronous time domain; and an adaptation module configured toadapt each of the tap coefficients as the leaky function for each tapcoefficient summed with a signal-dependent updating function for eachtap coefficient calculated in a synchronous time domain having a secondsampling rate and interpolated into the asynchronous time domain. 10.The system of claim 9, further comprising a signal-dependent updatingfunction module configured to calculate an error signal for each tapsignal as the difference between the equalized signal interpolated intothe synchronous time domain and an estimated signal, wherein theestimated signal is calculated from the equalized signal interpolatedinto the synchronous time domain and has a target signal type selectedfrom a (1−D²) partial response class-4 (“PR4”)polynomial, where Ddenotes delay by one symbol interval, a (1+D−D²−D³) extended PR4(“EPR4”) polynomial, a (1+2D−2D³−D⁴) extended EPR4 (“EEPR4”) polynomial,a generalized partial-response (“GPR”) polynomial with nonintegercoefficients, and a GPR polynomial for noise-predictivemaximum-likelihood (“NPML”) detection.
 11. The system of claim 10,wherein the signal-dependent updating function is (−αe_(n)x_(n−i)) whereα is a constant parameter, e_(n) is the error signal for the tap signal,and x_(n−i) is the tap signal, and wherein the leaky function of eachtap coefficient is c_(i,n)−αμƒ(c_(i,n)) where μ is a constant parameter,and ƒ(c_(i,n)) is a coefficient function of each tap coefficient c_(i,n)for the tap signal.
 12. A method for deploying computer infrastructure,comprising integrating computer-readable code into a computing system,the computing system comprising a processor and a memory, wherein thecode in combination with the computing system is capable of performingthe following: summing products of a plurality of tap signals from adelay line sampling a read signal and a plurality of corresponding tapcoefficients to form an equalized signal in an asynchronous time domainhaving a first sampling rate; calculating a leaky function for each tapcoefficient in the asynchronous time domain; and adapting each of thetap coefficients as the leaky function for each tap coefficient summedwith a signal-dependent updating function for each tap coefficientcalculated in a synchronous time domain having a second sampling rateand interpolated into the asynchronous time domain.
 13. The method ofclaim 12, wherein the signal-dependent updating function comprisescalculating an error signal for each tap signal as the differencebetween the equalized signal interpolated into the synchronous timedomain and an estimated signal.
 14. The method of claim 13, wherein theestimated signal is calculated from the equalized signal interpolatedinto the synchronous time domain and has a target signal type selectedfrom a (1−D²) partial response class-4 (“PR4”)polynomial, where Ddenotes delay by one symbol interval, a (1+D−D²−D³) extended PR4(“EPR4”) polynomial, a (1+2D−2D³−D⁴) extended EPR4 (“EEPR4”polynomial, ageneralized partial-response (“GPR”) polynomial with nonintegercoefficients, and a GPR polynomial for noise-predictivemaximum-llikelihood (“NPML”) detection.
 15. The method of claim 14,wherein the signal-dependent updating function is calculated as(−αe_(n)x_(n−i)) where α is a constant parameter, e_(n) is the errorsignal for the tap signal, and x_(n−i) is the tap signal, and whereinthe leaky function of each tap coefficient is c_(i,n)−αμƒ(c_(i,n)) whereμ is a constant parameter, and ƒ(c_(i,n)) is a coefficient function ofeach tap coefficient c_(i,n) for the tap signal.
 16. The method of claim15, wherein the coefficient function ƒ(c_(i,n)) is equal to c_(i,n). 17.The method of claim 15, wherein the coefficient function ƒ(c_(i,n)) isequal to the sign of c_(i,n).
 18. The method of claim 15, wherein μ isselected so that αμ is in the range of 0.0001 to 0.2 and αμ controls atap leakage process.
 19. The method of claim 12, further comprisinglimiting the absolute value of each tap coefficient.
 20. The method ofclaim 12, further comprising fixing at least one tap coefficient. 21.The method of claim 12, wherein the first sampling rate is greater thanthe second sampling rate.
 22. The method of claim 21, wherein the secondsampling rate is a symbol-sampling rate.
 23. A computer readable mediumtangibly embodying a program of machine-readable instructions executableby a digital processing apparatus to perform an operation to adapt tapcoefficients, the operation comprising: summing products of a pluralityof tap signals from a delay line sampling a read signal and a pluralityof corresponding tap coefficients to form an equalized signal in anasynchronous time domain having a first sampling rate; calculating aleaky function for each tap coefficient in the asynchronous time domain,wherein the leaky function of each tap coefficient is an operationc_(i,n)−αμƒ(c_(i,n)) where μ is a constant parameter, and ƒ(c_(i,n)) isa coefficient function operation of each tap coefficient c_(i,n); andadapting each of the tap coefficients as the leaky function for each tapcoefficient summed with a signal-dependent updating function for eachtap coefficient calculated in a synchronous time domain having a secondsampling rate and interpolated into the asynchronous time domain,wherein the signal-dependent updating function comprises an operation tocalculate an error signal for each tap signal as the difference betweenthe equalized signal interpolated into the synchronous time domain andan estimated signal.
 24. The signal bearing medium of claim 23, furthercomprising an operation to calculate the estimated signal from theequalized signal interpolated into the synchronous time domain and has atarget signal type selected from a partial response class-4 (“PR4”)polynomial, an extended PR4 (“EPR4”) polynomial, an extended EPR4(“EEPR4”) polynomial, a generalized partial-response (“GPR”) polynomialwith noninteger coefficients, and a GPR polynomial for noise-predictivemaximum-likelihood (“NPML”) detection.
 25. The computer readable mediumof claim 23, wherein the signal-dependent updating function is anoperation (−αe_(n)x_(n−i)) where α is a constant parameter, e_(n) is theerror signal for the tap signal, and x_(n−i) is the tap signal.
 26. Thecomputer readable medium of claim 23, wherein the coefficient functionƒ(c_(i,n)) is equal to c_(i,n).
 27. The computer readable medium ofclaim 23, wherein the coefficient function ƒ(c_(i,n)) is equal to thesign of c_(i,n).
 28. The computer readable medium of claim 23, wherein μis selected so that αμ is in the range of 0.0001 to 0.2 and αμ controlsa tap leakage process.
 29. The computer readable medium of claim 23,further comprising an operation to fix at least one tap coefficient. 30.An apparatus to adapt tap coefficients, the apparatus comprising: meansfor summing products of a plurality of tap signals from a delay linesampling a read signal and a plurality of corresponding tap coefficientsto form an equalized signal in an asynchronous time domain having afirst sampling rate; means for calculating a leaky function for each tapcoefficient in the asynchronous time domain, wherein the leaky functionof each tap coefficient is calculated as c_(i,n)−αμƒ(c_(i,n)) where μ isa constant parameter, and ƒ(c_(i,n)) is a coefficient function operationof each tap coefficient c_(i,n); and means for adapting each of the tapcoefficients as the leaky function for each tap coefficient summed witha signal-dependent updating function for each tap coefficient calculatedin a synchronous time domain having a second sampling rate andinterpolated into the asynchronous time domain, wherein thesignal-dependent updating function is calculated as (−αe_(n)x_(n−i))where α is a constant parameter, e_(n) is the error signal for the tapsignal, and x_(n−i) is the tap signal.